Machine-learning based tap detection
US9235278B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 24, 2014 |
| Grant date | Jan 12, 2016 |
| Priority date | — |
| Expiry date | Jul 24, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2200/1636
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An electronic device can be configured to enable a user to provide input via a tap of the device without the use of touch sensors (e.g., resistive, capacitive, ultrasonic or other acoustic, infrared or other optical, or piezoelectric touch technologies) and/or mechanical switches. Such a device can include other sensors, including inertial sensors (e.g., accelerometers, gyroscopes, or a combination thereof), microphones, proximity sensors, ambient light sensors, and/or cameras, among others, that can be used to capture respective sensor data. Feature values with respect to the respective sensor data can be extracted, and the feature values can be analyzed using machine learning to determine when the user has tapped on the electronic device. Detection of a single tap or multiple taps performed on the electronic device can be utilized to control the device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.